• Journal of Advanced Navigation Technology
• /
• v.23 no.3
• /
• pp.237-244
• /
• 2019

Since SBAS provides users with GNSS orbit, clock, and ionospheric corrections and integrity, the more precise positioning is possible. As the SBAS service area is expanded due to the development of the SBAS and the installation of the additional ground stations, there is a region where two or more SBAS messages can be received. However, the research on multi-constellation SBAS selection method has not carried out. In this study, we compared the result of positioning accuracy after applying the SBAS correction selected by using WAAS priority, EGNOS priority, or error covariance comparison method to LEO satellites in the regions where WAAS and EGNOS signals are transmitted simultaneously. When using WAAS priority method, 3D orbit error is smallest at 2.57 m. The covariance comparison method is outperform at the center of the overlap region far from each WAAS and EGNOS stations. In the eastern region near the EGNOS stations, the 3D orbit errors using EGNOS priority method is 8% smaller than the errors using the WAAS priority method.

• Journal of Advanced Navigation Technology
• /
• v.19 no.1
• /
• pp.15-21
• /
• 2015

WA-DGNSS is a system to service for users using a satellite which received correction data from ground station that calculates the relative errors of the tracked GNSS signals and sends to a satellite. Users are guaranteed the reliability of the GNSS signal and the accuracy of positioning. ICAO recommends the application of WA-DGNSS for the airplane taking off and landing process. In this paper, we suggests methods to verify of the pre-developed WA-DGNSS reference software constituting modules and an integration test process refer to the RTCA DO-278 which is a document for the development process of an aeronautics software. Also, we statistically verified the reference software test through our methods. And then, we confirmed to performance the function of the reference software properly.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2012.10a
• /
• pp.374-377
• /
• 2012

GNSS(Global Navigation Satellite System) based land transportation infrastructure system is consists of receiving station and central station. The functions of the central system include receiving station's data gathering and decoding, carrier correction and integrity information generated, transmission of data in real-time. In general, The central station architecture should take into account various important points relating to hardware/software of system, data archiving and checking, availability and continuity of operation, etc. There is a fundamental need for a generic design capable of being used in any situation. Also, There is need to develop an expandable and interoperable central station architecture. In this paper, the process of design and manufacture and verification will be introduced.

• Atmosphere
• /
• v.32 no.3
• /
• pp.191-206
• /
• 2022

Assimilation trials were performed using the Korea Institute of Atmospheric Prediction Systems (KIAPS) Korea Integrated Model (KIM) semi-operational forecast system to assess the impact of ground-based Global Navigation Satellite System (GNSS) Zenith Total Delay (ZTD) on forecast. To use the optimal observation in data assimilation of KIM forecast system, in this study, the ZTD observation were pre-processed. It involves the bias correction using long term background of KIM, the quality control based on background and the thinning of ZTD data. Also, to give the effect of observation directly to data assimilation, the observation operator which include non-linear model, tangent linear model, adjoint model, and jacobian code was developed and verified. As a result, impact of ZTD observation in both analysis and forecast was neutral or slightly positive on most meteorological variables, but positive on geopotential height. In addition, ZTD observations contributed to the improvement on precipitation of KIM forecast, specially over 5 mm/day precipitation intensity.

• Journal of Positioning, Navigation, and Timing
• /
• v.6 no.4
• /
• pp.159-166
• /
• 2017

The position of autonomous driving vehicle is basically acquired through the global positioning system (GPS). However, GPS signals cannot be received in tunnels. Due to this limitation, localization of autonomous driving vehicles can be made through sensors mounted on them. In particular, a 3D Light Detection and Ranging (LIDAR) system is used for longitudinal position error correction. Few feature points and structures that can be used for localization of vehicles are available in tunnels. Since lanes in the road are normally marked by solid line, it cannot be used to recognize a longitudinal position. In addition, only a small number of structures that are separated from the tunnel walls such as sign boards or jet fans are available. Thus, it is necessary to extract usable information from tunnels to recognize a longitudinal position. In this paper, fire hydrants and evacuation guide lights attached at both sides of tunnel walls were used to recognize a longitudinal position. These structures have highly distinctive reflectivity from the surrounding walls, which can be distinguished using LIDAR reflectivity data. Furthermore, reflectivity information of tunnel walls was fused with the road surface reflectivity map to generate a synthetic reflectivity map. When the synthetic reflectivity map was used, localization of vehicles was able through correlation matching with the local maps generated from the current LIDAR data. The experiments were conducted at an expressway including Maseong Tunnel (approximately 1.5 km long). The experiment results showed that the root mean square (RMS) position errors in lateral and longitudinal directions were 0.19 m and 0.35 m, respectively, exhibiting precise localization accuracy.

• Korean Journal of Remote Sensing
• /
• v.37 no.5_1
• /
• pp.1135-1147
• /
• 2021

In order to geometrically correct high-resolution satellite imagery, the sensor modeling process that restores the geometric relationship between the satellite sensor and the ground surface at the image acquisition time is required. In general, high-resolution satellites provide RPC (Rational Polynomial Coefficient) information, but the vendor-provided RPC includes geometric distortion caused by the position and orientation of the satellite sensor. GCP (Ground Control Point) is generally used to correct the RPC errors. The representative method of acquiring GCP is field survey to obtain accurate ground coordinates. However, it is difficult to find the GCP in the satellite image due to the quality of the image, land cover change, relief displacement, etc. By using image maps acquired from various sensors as reference data, it is possible to automate the collection of GCP through the image matching algorithm. In this study, the RPC of KOMPSAT-3A satellite image was corrected through the extracted matching point using the UAV (Unmanned Aerial Vehichle) imagery. We propose a pre-porocessing method for the extraction of matching points between the UAV imagery and KOMPSAT-3A satellite image. To this end, the characteristics of matching points extracted by independently applying the SURF (Speeded-Up Robust Features) and the phase correlation, which are representative feature-based matching method and area-based matching method, respectively, were compared. The RPC adjustment parameters were calculated using the matching points extracted through each algorithm. In order to verify the performance and usability of the proposed method, it was compared with the GCP-based RPC correction result. The GCP-based method showed an improvement of correction accuracy by 2.14 pixels for the sample and 5.43 pixelsfor the line compared to the vendor-provided RPC. In the proposed method using SURF and phase correlation methods, the accuracy of sample was improved by 0.83 pixels and 1.49 pixels, and that of line wasimproved by 4.81 pixels and 5.19 pixels, respectively, compared to the vendor-provided RPC. Through the experimental results, the proposed method using the UAV imagery presented the possibility as an alternative to the GCP-based method for the RPC correction.

• Journal of Advanced Navigation Technology
• /
• v.19 no.6
• /
• pp.465-472
• /
• 2015

In order to improve the performance of TCAS it should improve the performance of the sensor, which transmits a variety of information. In this paper, To improve the performance of the existing radar sensors such as being used in behalf of the next generation air traffic control system, ads-b the applied. In addition, ADS-B in a high precision by using information from the correction GPS system, SBAS assume would be able to apply an improved location accuracy for TCAS and analyzed TCAS and ADS-B. Played the simulation results, TCAS equipment receives the help of these ADS-B can calculate a CPA to determine the position of the aircraft in advance, and it was confirmed that it is possible to reduce the unnecessary RA operation, also, the pilot reduction and the workload, it has advantages such as fuel consumption and time associated with the reduced operation unnecessary RA was confirmed.

• Korean Journal of Remote Sensing
• /
• v.37 no.5_2
• /
• pp.1235-1243
• /
• 2021

Geostationary Ocean Color Imager 2 (GOCI-II) on Geo-KOMPSAT-2 (GK2B)satellite was developed as a mission successor of GOCI on COMS which had been operated for around 10 years since launch in 2010 to observe and monitor ocean color around Korean peninsula. GOCI-II on GK2B was successfully launched in February of 2020 to continue for detection, monitoring, quantification, and prediction of short/long term changes of coastal ocean environment for marine science research and application purpose. GOCI-II had already finished IAC and IOT including early in-orbit calibration and had been handed over to NOSC (National Ocean Satellite Center) in KHOA (Korea Hydrographic and Oceanographic Agency). Radiometric calibration was periodically conducted using on-board solar calibration system in GOCI-II. The final calibrated gain and offset were applied and validated during IOT. And three video parameter sets for one day and 12 video parameter sets for a year was selected and transferred to NOSC for normal operation. Star measurement-based INR (Image Navigation and Registration) navigation filtering and landmark measurement-based image geometric correction were applied to meet the all INR requirements. The GOCI2 INR software was validated through INR IOT. In this paper, status and results of IOT, radiometric calibration and INR of GOCI-II are analysed and described.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2008.05a
• /
• pp.197-200
• /
• 2008

A GNSS augmentation system provides precise position information using corrected GNSS pseudorange measurements. Common bias errors are corrected by PRC (Pseudorange Correction) between reference stations and a rover. However non-common errors (Ionospheric and Tropospheric noise error) are not corrected. Using position error variance this paper analyzes non-common errors (noise errors) of ionosphere and troposphere wet vapor.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.12 no.6
• /
• pp.1045-1050
• /
• 2008

A GNSS augmentation system provides precision information using corrected GNSS pseudorange measurements. Common bias errors are corrected by PRC (Pseudorange Correction) between reference stations and a rover. However non-common errors (ionospheric and tropospheric noise error) are not corrected. Using position error variance this paper analyzes non-common error (noise errors) of ionosphere and troposphere wet vapor.